Moxi

MOXI is an AI butler for your social life, creating a leading group experience planner accessed via your favourite messaging app.

Raised

Target Investment

Number of Investors

SEIS and/or EIS

Website

10

%

£150,000

1

Yes


Mission statement

MOXI is an AI butler for your social life, creating a leading group experience planner accessed via your favourite messaging app. 


High Level Overview
MOXI is an AI butler for your social life, accessed via your favourite messaging app. It's a personal concierge chatbot, searching for activities that you and your friends enjoy, at a time that suits and organising everyone for you.

MOXI is Doodle on steroids, delivering collaborative decision making paired with easy group payments, controlling the whole user experience journey to disrupt the £96Bn group experience market in the UK, and generating revenue with a freemium model as well as all in-app transactions.

And like any good butler it understands you and your friends and proactively anticipates needs, actually generating demand and providing a truly personalised service


Team

CEO - Adrian Wong (Leader of multi-disciplinary teams in agencies, startups and enterprise. Launched a global online gaming product in a saturated market securing one million users in 15 months. Designed AI voice chatbots for Enterprise


Strategic Advisor - Neil Ruth (COO @ Taptrip - An extensive background across travel and travel technology and has formed numerous strategic partnerships)


Technical Advisor - Andrew Rochester (Head of Engineering, Digital & Enterprise Service @ Royal Bank of Scotland - A strategic leader in several major corporations, driving digital and organisational transformation at scale, including launching a mobile banking app used by more than 10 million customers


Traction

Sales/revenue - pre-launch: 150+ Early Signups

Notable partners - Weavr.io: cutting edge virtual cards and group payments provider

USP - Group Focus/Automation & Optimisation/Predictive: MOXI doesn’t just service demand, it generates demand by anticipating needs

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